BRPI0720778A2 - CHANNEL QUALITY REALIMENT TECHNIQUES FOR A WIRELESS SYSTEM - Google Patents

Description

Report of the Invention Patent for "CHANNEL QUALITY REALIMENTAL TECHNIQUES FOR A WIRELESS SYSTEM".

Background

Wireless access networks that use a multi-carrier access technique, such as Orthogonal Frequency Division Multiple Access (OFDMA), allow the subchannels and time slots of an OFDMA frame to be assigned to multiple users. Subchannel quality and data transfer speed achievable for each user may vary over time. Channel Quality Indicator (CQI) is a measure of subchannel quality. Subchannels can be allocated to users based on a variety of factors including but not limited to CQI1. For example, CQI can be used to determine an appropriate modulation and coding (MCS) scheme to be applied to signals transmitted to a receiver. CQI communication, however, uses bandwidth that might otherwise be used to communicate other information such as data. Consequently, it is desirable to communicate CQI efficiently while considering available bandwidth limitations. Brief Description of the Drawings

Figure 1 illustrates one embodiment of an OFDMA resource.

Figure 2 illustrates one embodiment of a split chart.

Figure 3 illustrates one embodiment of a first correlation ratio graph.

Figure 4 illustrates one embodiment of a second correlation ratio graph.

Figure 5 illustrates one embodiment of a wireless communication system.

Figure 6 illustrates one embodiment of a first logical flow.

Figure 7 illustrates one embodiment of a second logical flow.

Figure 8 illustrates one embodiment of a third logical flow. Detailed Description

Various embodiments may comprise one or more elements. An element may comprise any feature, feature, structure or operation described in connection with an embodiment. Examples of elements may include hardware elements, software elements, physical elements, or any combination of them. However, one embodiment may be described with a limited number of elements in a certain arrangement by way of example, the embodiment may include more or less elements in alternative arrangements as desired for a given implementation. It is important to note that any references to "one embodiment" are not necessarily referring to the same embodiment.

Various embodiments can generally be directed to channel quality information feedback techniques for a wireless communication system. Some embodiments may be particularly directed to an adaptive scheduling algorithm to adaptably determine an amount of channel quality information feedback needed to achieve a desired probability of sub-channel assignment based on system load and information. widespread allocation information. Some embodiments may provide techniques for improving the channel efficiency information feedback efficiency of both a subscriber station and a base station. Some embodiments also quantify the tradeoff between a channel quality information feedback amount and the efficiency of subchannel assignments. This facilitates design options that can reduce poor channel quality information feedback performance to prove system spectral efficiency while conserving valuable radio frequency (RF) resources in upstream and / or downlink channels in the system. .

In some embodiments, techniques are provided which are capable of determining a CQI feedback dimension value representing various resource blocks for an OFDMA system to be measured by a subscriber station based on a correlation ratio value, and send the CQI feedback dimension value to the subscriber station.

In some embodiments, techniques are provided which are capable of receiving a CQI feedback dimension value from a base station via a subscriber station, measuring a channel quality for one or more resource blocks for a system. OFDMA as indicated by the feedback dimension value CQI, and send a CQI representing channel quality measurements to the base station.

Various modalities can be used in various applications.

many different. Some embodiments may be used in conjunction with various devices and systems, for example, a transmitter, a receiver, a transceiver, a transceiver, a wireless communication station, a wireless communication device, an Access Point (AP). ), a modem, a wireless modem, a Personal Computer (PC), a desktop computer, a mobile computer, a laptop computer, a data card computer, a server computer, a handheld, a handheld device, a Personal Digital Assistant (PDA) device, a handheld PDA device, a network, a wireless network, a Local Area Network (LAN), a Wireless LAN (WLAN), a Metropolitan Area Network (MAN), a Wireless MAN (WMAN), an Extended Area Network (WAN), a Wireless WAN (WWAN), devices and / or networks operating in accordance with IEEE 802.11 standards, 802.11a, 802.11b, 802.11e, 802.11g, 802.11h, 802.11i, 802.11η, 802.16, 802.16d, 802.16d and 802.16m versions and / or versions future and / or derivatives and / or Long Term Evolution (LTE) of the above standards, a Personal Area Network (PAN), a Wireless PAN (WPAN), units and / or devices that are part of the WLAN and / PAN and / or WPAN indicated above, one-way and / or two-way radio communication systems, cellular radiotelephone communication systems, a cellular telephone, a cordless telephone, a Personal Communication Systems (PCS) device, a PDA device incorporating a wireless communication device, a Multiple Inputs and Multiple Outputs (MIMO) transceiver or device, a Single Input and Multiple Outputs (SIMO) transceiver or device 1 a Multiple Inputs and Single Outputs (MISO) transceiver or device ), a Transceiver or Multiple Receiver Chain (MRC) device 1 is a transceiver or device having "smart antenna" or multi-antenna technology, or similar. Some modalities may be used in conjunction with one or more types of signals and / or wireless communication systems, for example, Radio Frequency (RF) 1 Infrared (IR) 1 Frequency Division Multiplexing (FDM) 1 Orthogonal FDM ( OFDM) 1 Orthogonal Frequency Division Multiple Access (OFDMA), Time Division Multiplexing (TDM), Time Division Multiple Access (TDMA), Extended TDMA (E-TDMA), General Packet Radio Service (GPRS) 1 Extended GPRS, Code Division Multiple Access (CDMA) 1 Broadband CDMA (WCDMA) 1 CDMA 2000, Multiple Carrier Modulation (MDM) 1 Discrete Multitone (DMT) 1 Blue Tooth (RTM) 1 ZigBee (TM) 1 or similar. Some embodiments may be used on various other devices, devices, systems and / or networks.

In various embodiments, OFDMA base station or schedulers in broadband wireless systems, such as, but not limited to, 802.16e, 802.16m, or the Third Generation Partnership Project (3GPP) LTE, may allocating resource blocks comprising groups of subcarriers that are referred to as subchannels (802.16e) or blocks (LTE) in frequency and symbols or groups of symbols that are referred to as intervals (802.16e) or subframes (LTE) in time. The scalable OFDMA feature is two-dimensional, for example, including time domain OFDM symbols and frequency domain subcarriers. A receiving subscriber station can measure channel quality of transmitted resource blocks and provide a CQI to the base station, thus allowing the OFDMA scheduler to take advantage of channel variations in both time and frequency. CQI can represent a single resource block or multiple resource blocks as desired for a given implementation. In the latter case, for example, a codebook technique can be used to represent multiple resource blocks using a single CQI value. The modalities are not limited in this context.

In many embodiments, the use of channel-aware OFDMA schedulers implemented at the base station can significantly improve system capacity and spectral efficiency in cellular broadband wireless systems. These schedulers rely heavily on channel quality estimates or CQI provided by competing subscriber stations. The poor performance associated with CQI impacts the resource available for upstream data scaling and this has a limitation on how much CQI can be fed back. CQI feedback is therefore a critical feature in air interface design for wireless broadband cellular systems. The embodiments try to solve these and other problems by using techniques that control the amount and type of CQI feedback provided by subscriber stations to improve overall system performance.

Figure 1 illustrates an example of an OFDMA 100 resource. As shown in Figure 1, OFDMA 100 may comprise an allocated system bandwidth partitioned on a frequency y-axis in multiple subcarriers, subchannels, or 1- blocks. N, a subset of which is represented as 1-j, and partitioned on a χ axis by time intervals or 1-i subframes. At any given time interval, one or more CQI values for each subscriber station may be fed back to N subchannels or blocks. A resource block can be represented as one or more intervals / subchannels (self definition) q (i, j). Depending on a CQI feedback granularity level selected for an OFDMA system, the CQI can represent channel measurement information for one or more resource blocks. As used herein, the granularity of CQI feedback information may refer to the amount of subchannels, subcarriers, blocks, or other resource blocks measured by a subscriber station to generate one or more CQI values.

Theoretically, the CQI value should provide the base station scheduler with all the information needed to optimally scale subchannels or blocks for competing subscriber stations. In practical systems, however, the CQI value is typically feedback only to a subset of the available N subchannels because of feedback bandwidth limitations. As the number of available subchannels grows with system bandwidth, there is a practical limitation on the number of subchannels for which the CQI value can be reset.

There is a compensatory correlation or exchange between the CQI feedback quantity and the corresponding scaling gains that result from the availability of CQI at the desired level of CQI feedback granularity. A design challenge arises while trying to determine how much CQI feedback granularity is required to give an OFDMA scheduler sufficient flexibility to allocate the OFDMA 100 resource to multiple competing subscriber stations. In low mobility scenarios, channel-aware OFDMA schedulers can provide significant gains by exploiting frequency selectivity. The granularity of frequency selective CQI information determines the flexibility that the scheduler has in correlating the available resource to competing subscriber stations with the best channel conditions.

CQI feedback granularity can influence many aspects of an OFDMA system. For example, the granularity of CQI feedback determines the amount of poor performance required to signal this information. Typically, the amount of poor performance consumed by CQI feedback information increases as the number of competing subscriber stations in the OFDMA system increases. In another example, the granularity of CQI feedback determines the amount of OFDMA 100 resource left to scale data after accounting for poor CQI feedback performance. Also in another example, the granularity of CQI feedback determines the complexity of scaling resource blocks to competing subscriber stations and providing quality of service (QoS) guarantees.

In various embodiments, an OFDMA scheduler may be arranged to use an adaptive scheduling algorithm to improve the effectiveness of CQI feedback from subscriber stations to the base station. In some embodiments, the amount of CQI feedback is dynamically adjusted for the load on the wireless system. In some instances, the subchannel set selected for CQI feedback is selected based on the subscriber station's own channel quality as well as observing the channel quality of other allocated subchannels broadcast on the downlink.

Subchannel assignment efficiency can be quantified as a function of CQI feedback granularity. Simulation results demonstrate decreased gains in subchannel assignment efficiency in increasing CQI feedback granularity. As a result, some embodiments may use an IQC for a relatively small subset of subchannels to achieve most of the frequency selective scaling gain, such as in the order of 2 to 3 subchannels per subscriber station. Additionally, the amount of feedback typically is independent of the number of subchannels in the system. This is contrary to conventional techniques that operate on the assumption that poor CQI feedback performance increases with the amount of subchannels in the OFDMA system.

Figure 2 illustrates one embodiment of a two-part graph 200. Two-part graph 200 illustrates an example of correlation efficiency for an OFDMA system. The left side of Figure 2 illustrates a set of concurrent subscriber stations 1-4 and a set of OFDMA A-D resource blocks. Subscriber stations 1, 3 are providing CQI feedback for resource block A, while subscriber stations 2, 4 are providing CQI feedback for resource block C. None of subscriber stations 1-4 are providing CQI feedback for resource blocks. In this example, split graph 200 illustrates each subscriber station as connected only to subchannels within its feedback subset. The weight of each connection is determined by the CQI value. The OFDMA scheduling algorithm uses these weights and the desired scheduling metric to assign subchannels to competing subscriber stations. Since the split graph 200 is only partially connected and each subchannel can be allocated to only one subscriber station, however, the output of the scheduling algorithm can be represented by the right side of figure 2. In this case, the scheduling algorithm OFDMA allocates resource block A to subscriber station 1, and resource block C to subscriber station 4. Since there was no feedback for resource blocks B, D, the OFDMA scaling algorithm was unable to provide full correlation for subscriber stations 2, 3 because of part of the limited CQI feedback set.

A set of definitions can be used to further examine the relationship between CQI feedback and correlation results for an OFDMA scheduler. A feedback set for each subscriber station may comprise a set of subchannels for which CQI feedback is provided. A correlation set for each subscriber station may comprise a set of subchannels allocated by the OFDMA scheduler. The degree of connectivity or correlation between competing subscriber stations and allocated subchannels is determined by the size of the feedback set. The correlation length D is the number of subchannels assigned to competing subscriber stations by the OFDMA scaler. The correlation ratio ρ can be defined as ρ = D / min (Μ, N), with the correlation ratio being lower when M = N.

One objective is to determine the relationship between the degree of connectivity and the maximum correlation extent. Consider the case when a subscriber station provides CQI feedback for the best subchannel without prior coordination with the base station. In this particular case, the degree of connectivity equals one (1) where each subscriber station reports exactly one subchannel (the best). In a system with M concurrent subscriber stations and N subchannels, one design consideration is the expected correlation extent to determine whether a subchannel can potentially be designated for each subscribing station.

The extent of correlation and its relationship to CQI feedback can be defined according to the following lemma or sub-side proposition, where if D subchannels are connected to at least one of the M subscriber stations, and if each subscriber station only connects to subchannel N, then the correlation extension is D. The probability that the correlation extension is D when each of the M subscriber stations provides CQI feedback information for only one of the N subchannels can be defined by the equation ( 1) as follows:

p (D | M, N) Equation (1) According to the definition provided by Equation (1), the probability of a correlation extension of one (1) can be represented by equation (2) as follows:

ι y / ι γ * · ■

p (\\ M, n) = n] - = - Equation (2)

no

f 1

V VV

no

VJV /

In order to develop an iterative expression for the probability of a correlation extension of D, consider the case when the user of order M is removed from the feedback set. If the order user M is not part of the correlation set, then the number of correlations is D even though the order user M is removed. On the other hand, if the user of order M is part of the correlation set, then the number of correlations is D-1, as shown in equation (3) as follows: p {d \ m, n) = —— ~ - ^ p (d- \\ m -1, n) + - ~ p (d \ m -1, ν) Equation (3)

When the number of subchannels K for which CQI is returned for each user is greater than 1, there is no closed solution to correlation extension D. Variable D, however, can be calculated by solving the problem. of two-way correlation for any given feedback pattern. This can be further described with reference to figures 3, 4.

When each subscriber feedback CQI corresponding to a subchannel, the probability that a subscriber station is not assigned a channel can be approximated by Equation (4) as follows:

Nj

Kl

Equation (4)

when N is relatively large. As the number of subchannels

for which CQI feedback information is provided grows to the

infinity and the system bandwidth grows to infinity (Μ = N - »oo), this probability approaches. As a result, when M = N - »oo,

The average number of subscriber stations to which a requested subchannel is assigned may be represented as Equation (5) which follows:

£> = tf (l-J /) Equation (5)

Consequently, when M = No then -> 1 - J /. In

In other words, if each subscriber station only feeds on the CQI corresponding to its best channel, approximately 63% of the subscribing stations can be assigned to subchannels from their feedback set. Thus, in some design cases this may represent an acceptable level of subchannel designation even with a reduced amount of CQI feedback information.

Figure 3 illustrates one embodiment of a correlation ratio graph 300. Correlation ratio graph 300 illustrates a correlation ratio between 0 and 1 on a y axis, and several subscriber stations (users) between 0 and 1. 35 on an axis χ. Correlation Ratio Graph 300 shows the correlation ratio when each of the M subscriber stations real- izes CQI corresponding to K of the total N subchannels at random. In general, the correlation ratio tends to decrease as M increases. The correlation ratio is the lowest when M = N. When K = I, the worst-case correlation ratio is approximately 63%. When K = 2, the worst-case correlation ratio improves to 85%. When K = 3, the worst-case correlation ratio further improves to 95%. From this information it can be seen that a reasonably good correlation ratio can be achieved if 2 or 3 good subchannels are fed back to each subscriber station. Figure 4 illustrates one embodiment of a correlation ratio graph 400. Correlation ratio graph 400 illustrates a correlation ratio between 0 and 1 on one y axis, and several subchannels between 0 and 64 on one axis. χ. Correlation Ratio Graph 400 shows the correlation ratio as a function of the number of subchannels Ν. The worst-case correlation ratio for M = N is plotted. As shown in Figure 4, when the number of subchannels is relatively small, such as when N <10, the worst-case correlation ratio is better than it is for larger values of Ν. Correlation Ratio Graph 400 clearly shows that the worst-case correlation ratio quickly converges to a constant for a given K feedback dimension. This saturation point occurs for a reasonably small number of subchannels. This suggests that increasing the number of subchannels to a desired worst-case correlation ratio has a decreased advantage. A relatively small feedback dimension of 3 results in the worst-case correlation ratio of approximately 95% or more. As illustrated, a larger CQI feedback dimension even results in a better worst-case correlation ratio result.

The above analysis provides a basis for adapting CQI feedback granularity to a base station's current system load. Since the base station is always aware of the number of competing subscriber stations, the number of subchannels to which CQI is being fed, and the correlation ratio at any time, it can broadcast a CQI K feedback dimension value to competing subscriber stations, where K represents the number of subchannels for which CQI feedback is required to achieve a desired correlation ratio. If the system load is lighter where the number of competing subscriber stations is lower, the CQI K feedback dimension value can be fed back to a larger number of subchannels to improve spectral efficiency without increasing low CQI feedback performance. beyond a desired threshold. On the other hand, if the system load is higher, the feedback dimension value CQI K may be reduced to increase the resource blocks available by OFDMA 100 to scale data and reduce poor feedback performance.

Figure 5 illustrates one embodiment of a wireless communication system 500. Wireless communication system 500 is an example of a wireless communication system suitable for implementing the adaptive scaling techniques described herein. As shown in Figure 5, the wireless communication system 500 includes a base station 520 and a subscriber station 550. For the sake of clarity only one of each base station 520 and each subscriber 550 is shown, but It may be appreciated that the wireless communication system 500 may include multiple base stations similar to base station 520, and multiple subscriber stations that are similar to subscriber station 550, as desired for a given implementation. By way of example and not limitation, the wireless communication system 500 may be implemented as a wireless access network using a multi-carrier access technique such as, but not limited to, these. , OFDM, or OFDMA. The modalities are not limited in this context.

In one embodiment, for example, wireless communication system 500 may comprise an OFDMA system where base station 520 can dynamically change the subscriber station 550 CQI feedback granularity depending on at least one current load for wireless communication system. 500. Base station 520 may communicate such changes to subscriber station 550 by means of a

CQI granularity 562.

In one embodiment, for example, base station 520 may include system configuration logic 502. System configuration logic 502 may be arranged to indicate an initial or standard set of one or more subchannels (K) for which CQI is to be measured by subscriber station 550. Modalities are not limited in this context.

In one embodiment, for example, base station 520 may include QoS requirements mapping logic and service flow 505. QoS requirements mapping logic and service flow 504 may be arranged to maintain quality of service information. and service flow for subscribers in a network. The modalities are not limited in this context.

In one embodiment, for example, base station 520 may include logic for managing requested resources and maintaining queue state 506. Requested resource logic and queue state 506 may be arranged to manage downlink and link link bandwidth allocated to subscriber stations such as subscriber station 550. Modalities are not limited in this context.

In one embodiment, for example, base station 520 may include a CQI management logic 510. CQI management logic 510 may be arranged to generate a message to be transmitted to subscriber stations to request CQI feedback from CQI. one or more subscriber stations for one or more subchannels based in part on the bandwidth allocated for use to provide CQI feedback. The modalities are not limited in this context.

In one embodiment, for example, base station 520 may include base station scheduler and frame assembler logic 512. Base station scheduler and frame assembler logic 512 may allocate bandwidth based on needs Subscriber Base station scheduler and frame assembler logic 512 can allocate a region in a subframe for each unique subscriber station. Base station scheduler and frame assembler logic 512 may indicate a location of a region in a subframe allocated to subscriber station 550. Base station scheduler and frame mount logic 512 may establish the width of bandwidth available for upstream communications from subscriber station 550 to base station 520 and vice versa. For example, to increase upstream data bandwidth, base station scheduler and frame mounter logic 512 may reduce bandwidth allocated for CQI communication. For example, to reduce bandwidth allocated for CQI1 communication, base station scheduler and frame assembler logic 512 may reduce CQI feedback granularity. Base station scheduler and frame assembler logic 512 can provide frames for transmission to subscriber station 550.

In various embodiments, base station 500 may transmit to subscriber station 550 various signals including, but not limited to, a CQI granularity signal 562 and a resource allocation signal 564. CQI granularity signal 562 may indicate the number of subchannels (K) for which subscriber station 550 is to make a CQI measurement. Resource allocation signal 564 may indicate to subscriber station 550 where data is located in a received frame.

In one embodiment, for example, subscriber station 550 may include scheduler logic and lease management 552. Scheduler logic and lease management 552 may perform various operations, such as monitoring downlink transmissions from the lease station. 520 to identify unassigned resource blocks, or designated resource blocks having a link quality below a defined link quality threshold, for example.

In one embodiment, for example, subscriber station 550 may include a CQI 554 measurement logic. Based on the CQI 562 granularity signal, the CQI 554 measurement logic may perform channel measurements to measure at least one CQI. the number of subchannels identified by the CQI 562 granularity signal. The CQI 554 measurement logic can be arranged to use any number of techniques for measuring channel quality indicators, such as, but not limited to, Ratio measurements. Noise Interference (SINR), Modulation and Coding Scheme (MCS) option selection, and instantaneous rate feedback.

Once the required channel measurements have been made, subscriber station 550 can indicate the CQI to base station 520 by transmitting a reporting signal CQI 566. The manner in which CQI is reported may conform to standards. such as, but not limited to, SINR measurements, Modulation and Coding Scheme (MCS) option selection, and instantaneous rate feedback.

Operations for apparatus 500 may be further described with reference to one or more logic flows. It may be understood that representative logical flows do not necessarily have to be executed in the order presented, or in any particular order, unless otherwise indicated. In addition, various activities described with respect to logical flows can be performed in series or parallel mode. Logical streams can be implemented using any desired hardware elements, software elements, or a combination of both.

Figure 6 illustrates a logical flow 600. The logical flow 600 may be representative of operations performed by one or more embodiments described herein, such as base station 520, for example. As shown in Figure 6, logic flow 600 can determine a CQI feedback dimension value representing several resource blocks for an OFDMA system to be measured by a subscriber station based on a correlation ratio value in block 602. Logical flow 600 may send the feedback dimension value CQI to the subscriber station in block 604. Modalities are not limited in this context.

In one embodiment, for example, base station scheduler and frame assembler logic 512 may determine a CQI feedback dimension value representing several resource blocks for an OFDMA system to be measured by a subscriber station based on a value. of correlation ratio. The correlation ratio value can represent a ratio indicating multiple subscriber stations allocated in a resource block relative to multiple subscriber stations requesting service for the wireless communication system 500 or multiple resource blocks allocated to the system. In general, base station scheduler and frame assembler logic 512 can increase the CQI feedback dimension value to increase the correlation ratio value, and decrease the realization dimension value. - CQI mentation to decrease the correlation ratio value. In one embodiment, for example, base station scheduler and frame assembler logic 512 may determine the correlation ratio value based on a subscriber station value representing several subscriber stations requesting service to the system. wireless communication 500, a correlation set value representing several resource blocks allocated to the wireless communication system 500, and / or a correlation extension value representing several resource blocks assigned to the subscriber stations. In some cases, the correlation ratio value may decrease as the subscriber station value increases.

In one embodiment, for example, base station scheduler and frame assembler logic 512 may send the feedback dimension value CQI to subscriber station 550. Base station and frame assembler scheduler logic 512 may receive an CQI representing a channel quality measurement for the resource blocks as indicated by the subscriber station 550 CQI feedback dimension value.

In addition to enhancing operations for an OFDMA scheduler at the base station by implementing the adaptive techniques described above, some embodiments may also improve operations for a subscriber station to increase channel feedback efficiency generated by subscriber station 550 and provided for base station 520. For example, consider the case when concorr competing subscriber stations feed back CQI corresponding to their most favorable K subchannels for base stations. As described with reference to Figure 2, some subscriber stations may have feedback sets overlapping. Depending on the scheduling algorithm, a subsequent allocation may not result in all K subchannels being allocated to subscriber stations as requested.

The base station typically broadcasts subchannel designations on the downlink channel. Each subscriber station can deduce useful information by generating a CQI feedback response. For example, each subscriber station may deduce whether a subchannel is allocated: (1) to the monitoring subscriber station; (2) some other subscriber stations; or (3) remains unassigned. In another example, each subscriber station may derive a rough estimate of the link quality of the assigned subchannels for other subscriber stations. This one mode can be realized by using the coding / modulation format (MCS) associated with the subchannel designation. If the number of subchannels assigned to a subscriber station is less than the number requested, it can improve the chance of allocation in the next routine by sending CQI feedback corresponding to any of the remaining unassigned subchannels, or the designated subchannels. to other subscriber stations with weaker link quality. If channel quality remains unchanged in previously allocated subchannels, the subscriber station continues CQI feedback on the designated channels. Such techniques can be described in more detail with reference to figure 7.

Figure 7 illustrates one embodiment of a logical flow 700. The logical flow 700 may be representative of operations performed by one or more embodiments described herein, such as subscriber station 550, for example. As shown in Fig. 7, logic flow 700 may receive a CQI feedback dimension value from a base station via a subscriber station in block 702. Logic flow 700 may measure a channel quality for one or more blocks. resources of an OFDMA system as indicated by the CQI reset dimension value in block 704. Logical stream 700 may send a CQI representing channel quality measurements to the base station in block 706. Modalities are not limited in this context.

In one embodiment, for example, the CQI 554 measurement logic may measure a channel quality for a resource block feedback set for the wireless communication system 500 as indicated by the CQI feedback dimension value via the signal. CQI 562. The feedback set may include a number of unassigned resource blocks as indicated by the CQI feedback dimension value. Alternatively, the feedback set may include several resource blocks fixed for other subscribers with a lower link quality value as indicated by the feedback dimension value CQI.

In one embodiment, for example, scheduler and lease management logic 552 can monitor and identify unassigned resource blocks by monitoring base station downlink transmissions 520. Measurement logic CQI 554 can measure a quali - channel capacity for a quantity of unassigned resource blocks as indicated by the feedback dimension value CQI. In this way, subscriber station 550 may increase a likelihood of base station 520 of allocating one or more of the unassigned resource blocks to subscriber station 550 during the next cycle.

In one embodiment, for example, scheduler logic and lease management 552 can identify designated resource blocks having a link quality value less than a defined link quality value. CQI 554 Measurement Logic can measure a channel quality for a number of the designated resource blocks as indicated by the CQI feedback dimension value. In this way, subscriber station 550 may increase the likelihood of base station 520 of relocating one or more of the designated resource blocks of a lower link quality subscriber to higher subscriber station 550. bond quality during the next cycle.

Figure 8 illustrates one embodiment of a logical flow 800. The logical flow 800 may be representative of an exemplary implementation for the adaptive technique performed by subscriber station 550. As shown in figure 8, subscriber station 550 may select K subchannels and transmit a CQI to base station 520 in block 802. Base station 520 broadcasts a subchannel allocation based on an adaptive scaling algorithm and the CQI information in the next frame in block 804. Three Separate execution paths can occur sequentially or in parallel.

In a first execution path, subscriber station 550 identifies a set K (a) of subchannels that have been requested and allocated in block 806. Subscriber station 550 identifies a set K (c) of subchannels for which the CQI has further degraded of a certain threshold and K (a) - K (c) for which CQI has not significantly degraded in block 808. Subscriber station 550 continues to send a CQI for K (a) - K (c) subchannels in block 810. A determination is made as if K (a) - K (c) = K in diamond 812. If the determination is YES in block 812, logic flow 800 passes control to block 804.

However, if the determination is NO in block 812 a determination is made as if K (u) <K - [K (a) - K (c)] in block 816. If the determination is NO in block 816 , then subscriber station 550 sends a CQI to K - [K (a) -K (c) j subchannels in subchannels not designated in block 820, and logic flow 800 passes control to block 804.

If YES is determined in block 812, subscriber station 550 sends a CQI for K (u) subchannels not assigned in block 822. Subscriber station 550 sends a CQI for K - [K (a) - K (c) ] - K (u) subchannels at the K (w) subchannels in block 830, and logic flow 800 passes control to block 804.

In a second execution path, subscriber station 550 identifies a set K (u) of subchannels that have not been assigned to any subscriber station in block 814. The logic flow then passes control to diamond 816, and the logic flow 800 proceeds as described above.

In a third execution path, subscriber station 550 identifies a set K (o) of subchannels that have been allocated to other subscriber stations in block 824. The subscriber station identifies a set K (w) of subchannels that are assigned to stations. weaker subscribers and K (b) = K (o) - K (w) subchannels are assigned to stronger subscriber stations in block 826. In this case, subscriber station 550 does not send a CQI in the subchannels in K (b) to reduce the chance of collisions in block 828. Logical flow 800 then passes control to block 830, and logical flow proceeds as described above.

Some embodiments, such as apparatus 100, may be implemented as a part, component or subsystem of an electronic device. Examples of electronic devices may include, without limitation, a processing system, computer, server, workstation, device, terminal, personal computer, laptop, ultra-portable computer, handheld, personal digital assistant, television, digital television, signal converter unit, telephone, mobile phone, mobile phone, telephone set, wireless access point, base station, subscriber station, mobile subscriber center, radio network controller, router , interconnect device, communication port, bridge, switch, machine, or combination thereof. The modalities are not limited in this context.

In one embodiment, for example, a processing system may include one or more processors. A processor may comprise any hardware element or software element arranged to process information or data. Some examples of processors may include, without limitation, a complex instruction set computer microprocessor (CISC), a reduced instruction set computer microprocessor (RISC), a very long instructional word microprocessor (VLIW), a processor implementing a combination of instruction sets, or another processor device. In one embodiment, for example, the processor may be implemented as a general purpose processor. Alternatively, the processor may be implemented as a dedicated processor, such as a controller, microcontroller, embedded processor, a digital signal processor (DSP), a network processor, a media processor, a power processor, or a processor. (I / O), a media access control (MAC) processor, a radio baseband processor, a field programmable port array (FPGA), a programmable logic device (PLD), a Application Specific Integrated Circuit (ASIC) and so on. The modalities are not limited in this context.

In one embodiment, for example, a processing device may include one or more memory units coupled to the processors. A memory unit can be any hardware element arranged to store information or data. Some examples of memory units may include, without limitation, random access memory (RAM), dynamic RAM (DRAM), Double Data Rate DRAM (DDRAM), synchronous DRAM (SDRAM), static RAM (SRAM), memory only. Read-Only (ROM), Programmable ROM (PROM), Erasable Programmable ROM (EPROM), EEPROM, Compact Disc ROM (CD-ROM), Recordable Compact Disc (CD-R), Rewritable Compact Disc (CD-RW) ), flash memory (eg NOR or NAND flash memory), content addressable memory (CAM), polymer memory (eg ferroelectric polymer memory), phase shift memory (eg ovonic memory) , ferroelectric memory, silicon oxide and silicon nitride (SONOS) memory, disk (for example, floppy disk, hard disk drive, optical disk, magnetic disk, magneto-optical disk), or plate (for example, magnetic board, optical board), tape, cassette and so on. Modalities are not limited in this context.

Some embodiments, such as apparatus 100, may be implemented as part of a communication system. A communication system may comprise multiple logic devices arranged to transmit information or data to each other. When implemented as a wireless communication system, one or more logic devices may include various elements suitable for wireless communications, such as one or more antennas, transmitters, receivers, transceivers, radios, amplifiers, filters, wireless interfaces. communications and other wireless elements. A wireless communication system transmits information or data through wireless communication media such as one or more RF spectrum parts or bands, for example. When implemented as a wired communication system, one or more logic devices may include various elements suitable for wired communications, such as one or more input / output (I / O) adapters, physical connectors for connecting the I / O adapter. with corresponding wired communications media, communication interfaces, network interface card (NIC), and other wired elements. Examples of wired communications media may include wire, cable, metal conductors, printed circuit board (PCB), backplate, switch fabric, semiconductor material, twisted pair wires, coaxial cable, fiber optics, and so on. against. The modalities are not limited in this context.

Some embodiments may be implemented as a manufacturing article. The article of manufacture may include storage media for storing logic and / or data for performing various operations of one or more embodiments. Storage media can represent any storage media capable of storing data or information, such as volatile or nonvolatile memory, removable or non-removable memory, erasable or non-erasable memory, recordable or rewritable memory, and so on. Examples of storage media may include, without limitation, such examples as previously provided for memory units. In various embodiments, for example, the manufacturing article may comprise a magnetic disk, optical disk, flash memory or firmware containing computer program instructions suitable for execution by a general purpose processor or application-specific processor. Modalities, however, are not limited in this context.

Various modalities can be implemented using hardware elements, software elements, or a combination of both. Examples of hardware elements may include any of the examples as previously provided for a logic device, and additionally including microprocessors, circuits, circuit elements (e.g., transistors, resistors, capacitors, inductors, and so forth), circuits. integrated, logic gates, registers, semiconductor device, microprocessors, chip set and so on. Examples of software elements may include software components, programs, applications, computer programs, application programs, system programs, machine programs, operating system software, meter, firmware, software modules, routines, sub -routines, functions, methods, procedures, software interfaces, application programming interfaces (APIs), instruction sets, computer code, computer code, code segments, computer code segments, words, values, symbols, or any combination thereof. Determining whether a modality is implemented using hardware elements and / or software elements may vary according to any number of factors, such as desired computational rate, power levels, heating tolerances, processing cycle budget, load ratios. input data, output data rates, memory resources, data bus speeds, and other design or performance constraints as desired for a given implementation.

Some embodiments may be described using the term "coupled" and "connected" together with their derivatives. These terms are not necessarily intended as synonyms for each other. For example, some embodiments may be described using the terms "connected" and / or "coupled" to indicate that two or more elements are in direct physical or electrical contact with one another. The term "coupled", however, can also mean that two or more elements are not in direct contact with each other, but also still cooperate or interact with each other.

It is emphasized that the Summary Description is provided to be in accordance with 37 C.F.R. Section 1.72 (b) which requires a summary allowing the reader to quickly ascertain the nature of the technical description. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. Moreover, in the preceding Detailed Description, it can be seen that several features are used together in a single embodiment for the purpose of optimizing the description. This method of description is not to be construed as reflecting an intention in which the claimed embodiments require more resources than are expressly reported in each claim. Instead, as the following claims reflect, the inventive subject matter in question is found to be less than in all features of a single embodiment described. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim remaining as a separate preferred embodiment. In the appended claims, the terms "including" and "in which" are used as the common English equivalents of the respective terms "comprising" and "where", respectively. In addition, the terms "first", "second", "third" and so on are used merely as labels and are not intended to impose numerical requirements on their objectives.

Although the subject matter has been described in specific language for structural resources and / or methodological procedures, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific resources or procedures described above. Instead, the specific features and procedures described above are described as exemplary ways to implement the claims.

Claims (25)

1. Apparatus comprising a base station having base station logic for determining a channel quality indicator feedback dimension value representing several resource blocks for an orthogonal frequency division multiple access system at be measured by a subscriber station based on a correlation ratio value, and a transceiver for sending said channel quality indicator feedback dimension value to said subscriber station. Apparatus according to claim 1, said base station logic for increasing said channel quality indicator feedback dimension value for increasing said correlation ratio value. Apparatus according to claim 1, said base station logic for determining said correlation ratio value based on a subscriber station value representing several subscriber stations requesting service to said system, a color set value - relationship representing several resource blocks allocated to said system, and a correlation extension value representing various resource blocks assigned to said subscriber stations. Apparatus according to claim 1, comprising a subscriber station having subscriber station logic for receiving said channel quality indicator feedback dimension value, measuring a channel quality for one or more indicated resource blocks. said channel quality indicator feedback dimension value, and sending a channel quality indicator representing said channel quality measurements to said base station. Apparatus according to claim 1, comprising an omnidirectional antenna coupled to said transceiver. A method comprising: determining a channel quality indicator feedback dimension value representing multiple resource blocks for an orthogonal frequency division multiple access system to be measured by a subscriber station based on a value of correlation ratio; and sending said channel quality indicator feedback dimension value to said subscriber station. A method according to claim 6, comprising receiving a channel quality indicator representing a channel quality measurement for said resource blocks indicated by said channel quality indicator feedback dimension value of said station. subscriber. The method of claim 6, comprising increasing said channel quality indicator feedback dimension value to increasing said correlation ratio value. A method according to claim 6, comprising determining said correlation ratio value representing a ratio indicating several subscriber stations allocated in a resource block relative to several subscriber stations requesting service to said system or several resource blocks allocated to said system. A method according to claim 6, comprising determining said correlation ratio value based on a subscriber station value representing several subscriber stations requesting service to said system, a correlation set value representing several resource blocks allocated for said system, and a correlation extension value representing several resource blocks designated for said subscriber stations. The method of claim 6, comprising determining said correlation ratio value based on a subscriber station value representing several subscriber stations requesting service to said system, said correlation ratio value decreasing as the said subscriber station value increases. A method according to claim 6, comprising increasing said channel quality indicator feedback dimension value to increase said correlation ratio value. A method comprising: receiving a channel quality indicator feedback dimension value from a base station by a subscriber station; measuring a channel quality for one or more resource blocks for an orthogonal frequency division multiple access system as indicated by said channel quality indicator feedback dimension value; and sending a channel quality indicator representing said channel quality measurements to said base station. A method according to claim 13, comprising: identifying unassigned resource blocks; and measuring a channel quality for a quantity of said unassigned resource blocks as indicated by said channel quality indicator feedback dimension value. A method according to claim 13, comprising: identifying designated resource blocks having a link quality value less than a defined link quality value; and measuring a channel quality for a quantity of said designated resource blocks as indicated by said channel quality indicator feedback dimension value. 16. Article comprising a storage medium containing executed instructions enable a system to: determine a channel quality indicator feedback dimension value representing several resource blocks for an orthogonal frequency division multiple access system to be measured by a subscriber station based on a correlation ratio value; and sending said channel quality indicator feedback dimension value to said subscriber station. An article according to claim 16, further comprising instructions which enable the system to receive a channel quality indicator representing a channel quality measurement for said resource blocks indicated by said feedback dimension value. quality indicator channel of said subscriber station. The article of claim 16, further comprising instructions which are performed enable the system to increase said channel quality indicator feedback dimension value to increase said correlation ratio value. An article according to claim 16, further comprising instructions that are executed enable the system to determine said correlation ratio value representing a ratio indicating several subscriber stations allocated in a resource block relative to several subscriber stations requesting service to said system or various blocks of resources allocated to said system. An article according to claim 16, further comprising instructions that are executed enable the system to determine said correlation ratio value based on a subscriber station value representing several subscriber stations requesting service to said subscriber. system, a correlation set value representing several resource blocks allocated to said system, and a correlation extension value representing several resource blocks assigned to said subscriber stations. An article according to claim 16, further comprising instructions that are executed enable the system to determine said correlation ratio value based on a subscriber station value representing several subscriber stations requesting service to said subscriber. system, said correlation ratio value decreases as said subscriber station value increases. The article of claim 16, further comprising instructions which are performed enable the system to increase said channel quality indicator feedback dimension value to increase said correlation ratio value. 23. An article comprising a storage medium containing executed instructions enables a system to: receive a channel quality indicator feedback dimension value from a base station via a subscriber station; measuring a channel quality for one or more resource blocks for an orthogonal frequency division multiple access system as indicated by said channel quality indicator feedback dimension value; and sending a channel quality indicator representing said channel quality measurements to said base station. An article according to claim 16, further comprising instructions that are carried out enable the system to: identify unassigned resource blocks; and measuring a channel quality for a quantity of said unassigned resource blocks as indicated by said channel quality indicator feedback dimension value. The article of claim 16, further comprising instructions that are performed enable the system to: identify designated resource blocks having a link quality value less than a defined link quality value; and measuring a channel quality for a quantity of said designated resource blocks as indicated by said channel quality indicator feedback dimension value.